高斯噪聲的代碼如下：

def GaussianNoise(src,means,sigma):NoiseImg=srcrows=NoiseImg.shape[0]cols=NoiseImg.shape[1]for i in range(rows):for j in range(cols):NoiseImg[i,j]=NoiseImg[i,j]+random.gauss(means,sigma)if NoiseImg[i,j]< 0:NoiseImg[i,j]=0elif NoiseImg[i,j]>255:NoiseImg[i,j]=255return NoiseImg

椒鹽噪聲的函數定義如下：

def PepperandSalt(src,percetage):NoiseImg=srcNoiseNum=int(percetage*src.shape[0]*src.shape[1])for i in range(NoiseNum):randX=random.random_integers(0,src.shape[0]-1)randY=random.random_integers(0,src.shape[1]-1)if random.random_integers(0,1)<=0.5:NoiseImg[randX,randY]=0else:NoiseImg[randX,randY]=255 return NoiseImg

椒鹽噪聲總體代碼如下：

import cv2 import random from numpy import * def PepperandSalt(src,percetage):NoiseImg=srcNoiseNum=int(percetage*src.shape[0]*src.shape[1])for i in range(NoiseNum):randX=random.random_integers(0,src.shape[0]-1)randY=random.random_integers(0,src.shape[1]-1)if random.random_integers(0,1)<=0.5:NoiseImg[randX,randY]=0else:NoiseImg[randX,randY]=255 return NoiseImg def GaussianNoise(src,means,sigma):NoiseImg=srcrows=NoiseImg.shape[0]cols=NoiseImg.shape[1]for i in range(rows):for j in range(cols):NoiseImg[i,j]=NoiseImg[i,j]+random.gauss(means,sigma)if NoiseImg[i,j]< 0:NoiseImg[i,j]=0elif NoiseImg[i,j]>255:NoiseImg[i,j]=255return NoiseImg img=cv2.imread('C:/Users/Administrator/Desktop/12.jpg',0) img1=PepperandSalt(img,0.2) cv2.imwrite('C:/Users/Administrator/Desktop/3.jpg',img1) cv2.imshow('PepperandSalt',img1) cv2.waitKey(0)

加入椒鹽噪聲之后的運行結果如下：

高斯噪聲的代碼為：

import cv2 from numpy import shape import random def PepperandSalt(src,percetage):NoiseImg=srcNoiseNum=int(percetage*src.shape[0]*src.shape[1])for i in range(NoiseNum):randX=random.randint(0,src.shape[0]-1)randY=random.randint(0,src.shape[1]-1)if random.random_integers(0,1)<=0.5:NoiseImg[randX,randY]=0else:NoiseImg[randX,randY]=255 return NoiseImg def GaussianNoise(src,means,sigma,percetage):NoiseImg=srcNoiseNum=int(percetage*src.shape[0]*src.shape[1])for i in range(NoiseNum):randX=random.randint(0,src.shape[0]-1)randY=random.randint(0,src.shape[1]-1)NoiseImg[randX, randY]=NoiseImg[randX,randY]+random.gauss(means,sigma)if NoiseImg[randX, randY]< 0:NoiseImg[randX, randY]=0elif NoiseImg[randX, randY]>255:NoiseImg[randX, randY]=255return NoiseImg img=cv2.imread('C:/Users/Administrator/Desktop/12.jpg',0) img1=GaussianNoise(img,2,4,0.8) cv2.imwrite('C:/Users/Administrator/Desktop/3.jpg',img1) cv2.imshow('PepperandSalt',img1) cv2.waitKey(0)

加入高斯噪聲的運行結果為：

總結

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